[−][src]Trait opencv::hub_prelude::DTrees_SplitTrait
The class represents split in a decision tree.
Required methods
pub fn as_raw_DTrees_Split(&self) -> *const c_void
[src]
pub fn as_raw_mut_DTrees_Split(&mut self) -> *mut c_void
[src]
Provided methods
pub fn var_idx(&self) -> i32
[src]
Index of variable on which the split is created.
pub fn set_var_idx(&mut self, val: i32)
[src]
Index of variable on which the split is created.
pub fn inversed(&self) -> bool
[src]
If true, then the inverse split rule is used (i.e. left and right branches are exchanged in the rule expressions below).
pub fn set_inversed(&mut self, val: bool)
[src]
If true, then the inverse split rule is used (i.e. left and right branches are exchanged in the rule expressions below).
pub fn quality(&self) -> f32
[src]
The split quality, a positive number. It is used to choose the best split.
pub fn set_quality(&mut self, val: f32)
[src]
The split quality, a positive number. It is used to choose the best split.
pub fn next(&self) -> i32
[src]
Index of the next split in the list of splits for the node
pub fn set_next(&mut self, val: i32)
[src]
Index of the next split in the list of splits for the node
pub fn c(&self) -> f32
[src]
< The threshold value in case of split on an ordered variable. The rule is:
if var_value < c then next_node <- left else next_node <- right
pub fn set_c(&mut self, val: f32)
[src]
< The threshold value in case of split on an ordered variable. The rule is:
if var_value < c then next_node <- left else next_node <- right
pub fn subset_ofs(&self) -> i32
[src]
< Offset of the bitset used by the split on a categorical variable. The rule is:
if bitset[var_value] == 1 then next_node <- left else next_node <- right
pub fn set_subset_ofs(&mut self, val: i32)
[src]
< Offset of the bitset used by the split on a categorical variable. The rule is:
if bitset[var_value] == 1 then next_node <- left else next_node <- right